Scvitools

Acerca de

Provides comprehensive assistance for single-cell omics analysis using the scvi-tools suite. It streamlines the implementation of deep generative models like scVI, scANVI, and totalVI to handle complex tasks such as batch correction, data integration, and multimodal analysis including RNA-seq, ATAC-seq, and CITE-seq. Whether setting up AnnData objects, performing differential expression tests, or building custom model architectures, this skill offers the technical guidance and code patterns necessary to derive biological insights from high-dimensional single-cell datasets.

Características Principales

• 0 GitHub stars
• Advanced differential expression and abundance analysis workflows
• Custom model development and extension of scvi-tools base classes
• Automated hyperparameter tuning and model optimization via scvi.autotune
• Implementation of scVI, scANVI, totalVI, MultiVI, and GIMVI models
• Batch correction and data integration for multi-modal single-cell experiments

Casos de Uso

• Analyzing multimodal data such as CITE-seq or spatial transcriptomics with deep generative models
• Integrating disparate single-cell datasets while correcting for technical batch effects
• Developing specialized variational autoencoder architectures for unique biological questions